Search Results - (( variable optimization technique algorithm ) OR ( wave optimization path algorithm ))
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance
Published 2022“…An optimal path between the start and target point is found by forming a wave of points in all directions towards the target position considering target minimum and border maximum distance principles. …”
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…These models are developed by integrating multilayer perceptron neural network and evolutionary optimization techniques. Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2021“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems
Published 2017“…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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Research Report -
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Development of a State-Space Observer for Active Noise Control Systems
Published 2009“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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9
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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10
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. …”
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Levy slime mould algorithm for solving numerical and engineering optimization problems
Published 2022“…The proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
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Mixed variable ant colony optimization technique for feature subset selection and model selection
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River
Published 2025“…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”
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Efficient and scalable ant colony optimization based WSN routing protocol for IoT
Published 2020“…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…(i) what decision making models and (ii) what computational techniques, provide an optimal manufacturing process planning solution in a multidimensional decision variables space? …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
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Global Particle Swarm Optimization for High Dimension Numerical Functions Analysis
Published 2014“…The Particle Swarm Optimization (PSO) Algorithm is a popular optimization method that is widely used in various applications, due to its simplicity and capability in obtaining optimal results. …”
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An Application of Cuckoo Search Algorithm for Solving Optimal Chiller Loading Problem for Energy Conservation
Published 2014“…This paper presents a recent swarm intelligence technique viz. Cuckoo Search Algorithm (CSA) for solving the Optimal Chiller Loading (OCL) problem for energy conservation. …”
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A MODIFIED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR WELLBORE TRAJECTORY DESIGN
Published 2021“…To address this issue, a new hybridization of cellular automata (CA) technique with grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms is proposed in this work which solves these three optimization objectives of drilling through 17 tuning variables. …”
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